The GAN [1]} consists of a generator (G) and discriminator (D). The generator (G) in GAN learns the mapping between two data distributions with the help of discriminator. In the case of MRI reconstruction, the goal of the generator is to learn the mapping between the data distribution of the ZF image (\(x_{u}\) ) and FS image (\(x_{f}\) ). The discriminator learns to distinguish between the generated and target reconstruction.
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